Dataset Information

Is More Area-Level Crime Associated With More Sitting and Less Physical Activity? Longitudinal Evidence From 37,162 Australians.

ABSTRACT: Does a rise in crime result in increased sitting time and a reduction in physical activity? We used unobserved ("fixed")-effects models to examine associations between change in objectively measured crime (nondomestic violence, malicious damage, breaking and entering, and stealing, theft, and robbery) in Australia and measures of sitting time, walking, and moderate-to-vigorous physical activity (MVPA) in a residentially stable sample of 17,474 men and 19,688 women at baseline (2006-2008) and follow-up (2009-2010). Possible sources of time-varying confounding included age, income, economic status, relationship (couple) status, and physical functioning. In adjusted models, an increase in all crimes of 10 counts per 1,000 residents was associated with an increase in sitting time (hours/day) among men (? = 0.21, 95% confidence interval (CI): 0.17, 0.25) and women (? = 0.18, 95% CI: 0.15, 0.22). Counterintuitively, the same increase in crime was also associated with an increase in the weekly number of ?10-minute walking sessions (men: rate ratio (RR) = 1.01 (95% CI: 1.01, 1.02); women: RR = 1.00 (95% CI: 0.99, 1.01)) and MVPA sessions (men: RR = 1.02 (95% CI: 1.02, 1.03); women: RR = 1.01 (95% CI: 1.00, 1.02)). Similar associations were found for the other area-level crime indicators. While area-level crime prevention may be considered a lever for promoting more active lifestyles, these results suggest that the association is not unequivocal.

SUBMITTER: Astell-Burt T

PROVIDER: S-EPMC5161084 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Is More Area-Level Crime Associated With More Sitting and Less Physical Activity? Longitudinal Evidence From 37,162 Australians.

Astell-Burt Thomas T Feng Xiaoqi X Kolt Gregory S GS Jalaludin Bin B

American journal of epidemiology 20161117 12

Does a rise in crime result in increased sitting time and a reduction in physical activity? We used unobserved ("fixed")-effects models to examine associations between change in objectively measured crime (nondomestic violence, malicious damage, breaking and entering, and stealing, theft, and robbery) in Australia and measures of sitting time, walking, and moderate-to-vigorous physical activity (MVPA) in a residentially stable sample of 17,474 men and 19,688 women at baseline (2006-2008) and fol ...[more]

PMID: 27856450

Similar Datasets

Project description:BackgroundUrban greening may reduce loneliness by offering opportunities for solace, social reconnection and supporting processes such as stress relief. We (i) assessed associations between residential green space and cumulative incidence of, and relief from, loneliness over 4 years; and (ii) explored contingencies by age, sex, disability and cohabitation status.MethodsMultilevel logistic regressions of change in loneliness status in 8049 city-dwellers between 2013 (baseline) and 2017 (follow-up) in the Household, Income and Labour Dynamics in Australia study. Associations with objectively measured discrete green-space buffers (e.g. parks) (<400, <800 and <1600 m) were adjusted for age, sex, disability, cohabitation status, children and socio-economic variables. Results were translated into absolute risk reductions in loneliness per 10% increase in urban greening.ResultsThe absolute risk of loneliness rose from 15.9% to 16.9% over the 4 years; however, a 10% increase in urban greening within 1.6 km was associated with lower cumulative incident loneliness [odds ratio (OR) = 0.927, 95% confidence interval (CI) = 0.862 to 0.996; absolute risk reduction = 0.66%]. Stronger association was observed for people living alone (OR = 0.828, 95% CI = 0.725 to 0.944). In comparison to people with <10% green space, the ORs for cumulative incident loneliness were 0.833 (95% CI = 0.695 to 0.997), 0.790 (95% CI = 0.624 to 1.000) and 0.736 (95% CI = 0.549 to 0.986) for 10-20%, 20-30% and >30% green space, respectively. Compared with the <10% green-space reference group with 13.78% incident loneliness over 4 years and conservatively assuming no impact on incident loneliness, associations translated into absolute risk reductions of 1.70%, 2.26% and 2.72% within populations with 10-20%, 20-30% and >30% green space, respectively. These associations were stronger again for people living alone, with 10-20% (OR = 0.608, 95% CI = 0.448 to 0.826), 20-30% (OR = 0.649, 95% CI = 0.436 to 0.966) and >30% (OR = 0.480, 95% CI = 0.278 to 0.829) green space within 1600 m. No age, sex or disability-related contingencies, associations with green space within 400 or 800 m or relief from loneliness reported at baseline were observed.ConclusionsA lower cumulative incidence of loneliness was observed among people with more green space within 1600 m of home, especially for people living alone. Potential biopsychosocial mechanisms warrant investigation.

Project description:BackgroundClinical practice guidelines recommend that adults with type 2 diabetes (T2D) sit less and move more throughout the day. The 18-month OPTIMISE Your Health Clinical Trial was developed to support desk-based workers with T2D achieve these recommendations. The two-arm protocol consists of an intervention and control arms. The intervention arm receives 6 months health coaching, a sit-stand desktop workstation and an activity tracker, followed by 6 months of text message support, then 6 months maintenance. The control arm receives a delayed modified intervention after 12 months of usual care. This paper describes the methods of a randomised controlled trial (RCT) evaluating the effectiveness and cost-effectiveness of the intervention, compared to a delayed intervention control.MethodsThis is a two-arm RCT being conducted in Melbourne, Australia. Desk-based workers (≥0.8 full-time equivalent) aged 35-65 years, ambulatory, and with T2D and managed glycaemic control (6.5-10.0% HbA1c), are randomised to the multicomponent intervention (target n = 125) or delayed-intervention control (target n = 125) conditions. All intervention participants receive 6 months of tailored health coaching assisting them to "sit less" and "move more" at work and throughout the day, supported by a sit-stand desktop workstation and an activity tracker (Fitbit). Participants receive text message-based extended care for a further 6-months (6-12 months) followed by 6-months of non-contact (12-18 months: maintenance). Delayed intervention occurs at 12-18 months for the control arm. Assessments are undertaken at baseline, 3, 6, 12, 15 and 18-months. Primary outcomes are activPAL-measured sitting time (h/16 h day), glycosylated haemoglobin (HbA1c; %, mmol/mol) and, cognitive function measures (visual learning and new memory; Paired Associates Learning Total Errors [adjusted]). Secondary, exploratory, and process outcomes will also be collected throughout the trial.DiscussionThe OPTIMISE Your Health trial will provide unique insights into the benefits of an intervention aimed at sitting less and moving more in desk-bound office workers with T2D, with outcomes relevant to glycaemic control, and to cardiometabolic and brain health. Findings will contribute new insights to add to the evidence base on initiating and maintaining behaviour change with clinical populations and inform practice in diabetes management.Trial registrationANZCTRN12618001159246 .

Project description:BACKGROUND:Sleep and physical activity are modifiable behaviors that play an important role in preventing overweight, obesity, and metabolic health problems. Studies of the association between concurrent objective measures of sleep, physical activity, and metabolic risk factors among adolescents are limited. OBJECTIVE:The aim of the study was to examine the association between metabolic risk factors and objectively measured school day physical activity and sleep duration, quality, onset, and variability in adolescents. MATERIALS AND METHODS:We measured one school week of free-living sleep and physical activity with wrist actigraphy in 252 adolescents (146 girls), aged 15.8±0.3 years. Metabolic risk factors included body mass index, waist circumference, total body and trunk fat percentage, resting blood pressure, and fasting glucose and insulin levels. Multiple linear regression adjusted for sex, parental education, and day length was used to assess associations between metabolic risk factors and sleep and activity parameters. RESULTS:On average, participants went to bed at 00:22±0.88 hours and slept 6.2±0.7 hours/night, with 0.83±0.36 hours of awakenings/night. However, night-to-night variability in sleep duration was considerable (mean ± interquartile range) 0.75±0.55 hours) and bedtime (0.64±0.53 hours) respectively. Neither average sleep duration nor mean bedtime was associated with any metabolic risk factors. However, greater night-to-night variability in sleep duration and bedtime was associated with higher total body and trunk fat percentage, and less physical activity was associated with higher trunk fat percentage and insulin levels. CONCLUSION:Greater nightly variation in sleep duration and in bedtime and less physical activity were associated with a less favorable metabolic profile in adolescents. These findings support the idea that, along with an adequate amount of physical activity, a regular sleep schedule is important for the metabolic health of adolescents.

Dataset Information

Is More Area-Level Crime Associated With More Sitting and Less Physical Activity? Longitudinal Evidence From 37,162 Australians.

Publications

Is More Area-Level Crime Associated With More Sitting and Less Physical Activity? Longitudinal Evidence From 37,162 Australians.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets